feat(dolt): migration 026 + models — fundamentals/earnings schema (A1 schema)

First reviewable slice of workstream A: schema only, no importers, no data.

- data_import_runs: lean batch-import audit (source/revision/status,
  row_counts_json + validation_json as Text-holding-JSON per repo convention).
- fundamental_snapshots: CIK-keyed, one immutable row per accession; stores
  per-period raw facts (duration = cumulative YTD/FY, balance-sheet =
  period-end) plus period_start/period_end/fiscal_year/fiscal_period so
  discrete quarters, Q4, TTM and YoY are derived at read time.
- earnings_events: Dolt-sourced calendar + surprise history, unique
  (ticker_id, announce_date).
- tickers: nullable cik/sic/sic_description — the ticker<->issuer join point.

fundamental_data is left untouched (cutover gated separately at A5). Models
registered in app/models/__init__.py; Ticker gains an earnings_events
relationship. Verified: create_all builds the tables, mappers configure, and
migration 026 renders valid Postgres DDL up and down.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

app/models/earnings_event.py

@@ -0,0 +1,42 @@
+from datetime import date, datetime
+
+from sqlalchemy import Date, DateTime, Float, ForeignKey, Index, String, UniqueConstraint
+from sqlalchemy.orm import Mapped, mapped_column, relationship
+
+from app.database import Base
+
+
+class EarningsEvent(Base):
+    """Earnings calendar + surprise history, sourced from the DoltHub earnings repo.
+
+    Forward rows (``announce_date`` > today) are the calendar; past rows are
+    results. Rescheduling is handled in the importer's promotion transaction:
+    this source's future-dated rows are deleted and re-inserted from the new
+    snapshot so moved/cancelled dates never linger; past rows are never deleted.
+    """
+
+    __tablename__ = "earnings_events"
+    __table_args__ = (
+        UniqueConstraint("ticker_id", "announce_date", name="uq_earnings_ticker_announce"),
+        Index("ix_earnings_events_announce_date", "announce_date"),
+    )
+
+    id: Mapped[int] = mapped_column(primary_key=True)
+    ticker_id: Mapped[int] = mapped_column(
+        ForeignKey("tickers.id", ondelete="CASCADE"), nullable=False
+    )
+    announce_date: Mapped[date] = mapped_column(Date, nullable=False)
+    # bmo | amc | unknown (source coverage is partial)
+    session: Mapped[str] = mapped_column(String(10), nullable=False, default="unknown")
+    period_end: Mapped[date | None] = mapped_column(Date, nullable=True)
+    eps_estimate: Mapped[float | None] = mapped_column(Float, nullable=True)
+    eps_actual: Mapped[float | None] = mapped_column(Float, nullable=True)
+    source: Mapped[str] = mapped_column(String(32), nullable=False)
+    import_run_id: Mapped[int | None] = mapped_column(
+        ForeignKey("data_import_runs.id", ondelete="SET NULL"), nullable=True
+    )
+    created_at: Mapped[datetime] = mapped_column(
+        DateTime(timezone=True), default=datetime.utcnow, nullable=False
+    )
+
+    ticker = relationship("Ticker", back_populates="earnings_events")